Search results for "Geomatic"
showing 10 items of 506 documents
Exploring the Validity of the Long-Term Data Record V4 Database for Land Surface Monitoring
2016
A new version of the long-term data record (LTDR)—Version 4—has been released recently by NASA. This database includes daily information for all advanced very high resolution radiometer channels, as well as ancillary data, from July 1981 up to present. This dataset is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the daily estimation of vegetation indices, as well as the estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring, especially as regards long-term trends and their validity. To that end, we estimated normalized difference vegetation index (NDVI), LST, as well …
Evaluation of Disaggregation Methods for Downscaling MODIS Land Surface Temperature to Landsat Spatial Resolution in Barrax Test Site
2016
Thermal infrared (TIR) data are usually acquired at a coarser spatial resolution (CR) than visible and near infrared (VNIR). Several disaggregation methods have been recently developed to enhance the TIR spatial resolution using VNIR data. These approaches are based on the retrieval of a relation between TIR and VNIR data at CR, or training of a neural network, to be applied at the fine resolution afterward. In this work, different disaggregation methods are applied to the combination of two different sensors in the experimental test site of Barrax, Spain. The main objective is to test the feasibility of these techniques when applied to satellites provided with no TIR bands. Landsat and mod…
Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran
2017
Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach…
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…
A spatially consistent downscaling approach for SMOS using an adaptive window
2017
The European Space Agency (ESA)'s Soil Moisture and Ocean Salinity (SMOS) is the first spaceborne mission using L-band radiometry to monitor the Earth's global surface soil moisture (SM). After more than 7 years in orbit, many studies have contributed to improve the quality and applicability of SMOS-derived SM maps. In this research, a novel downscaling algorithm for SMOS is proposed to obtain high-resolution (HR) SM maps at 1 km (L4), from the ∼40 km native resolution of the instrument. This algorithm introduces the concept of a shape adaptive moving window as an improvement of the current semi-empirical downscaling approach at SMOS Barcelona Expert Center, based on the “universal triangle…
Consistency between GRUAN sondes, LBLRTM and IASI
2017
Abstract. Radiosonde soundings from the GCOS Reference Upper-Air Network (GRUAN) data record are shown to be consistent with Infrared Atmospheric Sounding Instrument (IASI)-measured radiances via LBLRTM (Line-By-Line Radiative Transfer Model) in the part of the spectrum that is mostly affected by water vapour absorption in the upper troposphere (from 700 hPa up). This result is key for climate data records, since GRUAN, IASI and LBLRTM constitute reference measurements or a reference radiative transfer model in each of their fields. This is specially the case for night-time radiosonde measurements. Although the sample size is small (16 cases), daytime GRUAN radiosonde measurements seem to h…
Integrated remote sensing approach to global agricultural drought monitoring
2018
Abstract This study explores the use of the Soil Moisture Agricultural Drought Index (SMADI) as a global estimator of agricultural drought. Previous research presented SMADI as a novel index based on the joint use of remotely sensed datasets of land surface temperature (LST) and normalized difference vegetation index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) together with the surface soil moisture (SSM) from the Soil Moisture and Ocean Salinity (SMOS) mission. This study presents the results of applying SMADI at the global scale with a spatial resolution of 0.05° every 15 days. The period of the study spanned from 2010 to 2015. Three spatial scales (local, region…
Efficient Kernel Cook's Distance for Remote Sensing Anomalous Change Detection
2021
Detecting anomalous changes in remote sensing images is a challenging problem, where many approaches and techniques have been presented so far. We rely on the standard field of multivariate statistics of diagnostic measures, which are concerned about the characterization of distributions, detection of anomalies, extreme events, and changes. One useful tool to detect multivariate anomalies is the celebrated Cook's distance. Instead of assuming a linear relationship, we present a novel kernelized version of the Cook's distance to address anomalous change detection in remote sensing images. Due to the large computational burden involved in the direct kernelization, and the lack of out-…
Comparative study of three satellite image time-series decomposition methods for vegetation change detection
2018
International audience; Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algori…
Multitemporal Mosaicing for Sentinel-3/FLEX Derived Level-2 Product Composites
2020
The increasing availability of remote sensing data raises important challenges in terms of operational data provision and spatial coverage for conducting global studies and analyses. In this regard, existing multitemporal mosaicing techniques are generally limited to producing spectral image composites without considering the particular features of higher-level biophysical and other derived products, such as those provided by the Sentinel-3 (S3) and Fluorescence Explorer (FLEX) tandem missions. To relieve these limitations, this article proposes a novel multitemporal mosaicing algorithm specially designed for operational S3-derived products and also studies its applicability within the FLEX…